What’s the real score on poverty?
In the wake of recent statistics on hunger, nutrition and child poverty, a respected senator called for a war on hunger. Palace officials quickly mentioned that welfare conditions are improving, saying that “while poverty incidence went down by only 0.2 points during the years of 2006 to 2009 and by only 0.7 points from 2009 to 2012, from 2012 to 2013 it dropped by three (percentage) points.”
In its Philippine Economic Update, August 2014 edition, the World Bank similarly described improving poverty conditions. "After many years of slow poverty reduction, poverty incidence among the population declined by 3 percentage points between 2012 and 2013 to 24.9 %, lifting 2.5 million Filipinos out of poverty," the WB said. "These poverty assessments follow an assertion from the National Economic and Development Authority (NEDA) about “a remarkable improvement in the poverty incidence in the first half of 2013.”
Truth be told, while these descriptions on poverty are based on official statistics released by the Philippine Statistics Authority (PSA), the April 2014 press release of the PSA did not actually report a “drop” in poverty incidence from 2012 to 2013. The PSA mentioned that “24.9% of Filipinos were poor in the first semester of 2013,” and that in “the same period in 2012, poverty incidence among Filipinos was recorded at 27.9 percent generated from the 2012 Family Income and Expenditure Survey (FIES).” But isn’t 24.9 percent a “decline” from 27.9 percent? Seemingly, yes, but in this case, no. To compare statistics, their methodologies should be equivalent. Otherwise, we are comparing apples and oranges.
The PSA’s technical notes point out that the source of poverty data on the first half of 2013 is the 2013 Annual Poverty Indicator Survey (APIS), another survey of the PSA, which used a different questionnaire from that of the 2012 FIES.
Table 1. Official Estimates of Poverty Incidence in the Philippines
|YEAR||FIRST SEMESTER||FULL CALENDAR YEAR||SOURCE||REMARKS|
|2012||27.9%||25.3%||2012 FIES||78 pages of questions (24 of which on income, 47 on expenditure)|
|2013||24.9%||2013 APIS||32 pages of questions (19 of which on income, 6 on expenditure)|
Although the 2013 APIS used more questions on income (than it used to) with its 19 pages of questions, the 2012 FIES income module used 24 pages of questions. However, even if APIS 2013 made use of the 24-page income module of FIES 2012, this would still not make poverty data from the APIS and FIES comparable since FIES also asks households detailed information on their expenditures (before income questions are asked) using a total of 78 pages of questions (taking an average interview time of 5 hours).
The APIS 2013 questionnaire had 6 pages of questions on expenditure, aside from 19 pages of income questions, and several pages of other questions, which, over all, took 3 hours to accomplish.
Consequently, official poverty statistics in the first semester of 2013 are incomparable to those based on the FIES 2012. We have apples and oranges here, so there is no certainty about a drop in poverty, as has been claimed.
On the other hand, can't we look at self-rated poverty from the Social Weather Stations (SWS) surveys? No, since these SWS statistics are based on showing respondents face cards with a line running across these cards. Below the line is marked “poor” and above the line, “nonpoor.” Each respondent is then asked, “Where would you place your family in this card?” SWS self-rated poverty statistics are likewise incomparable to income poverty statistics. Here, we have apples and bananas.
To get definitive recent trends on income poverty, we have to await the results of the 2014 APIS.
Unchanged poverty rates
Three clear trends on poverty conditions can, however, be seen from past runs of the FIES: (a) poverty rates have been unchanged in the first semester periods from 2006 to 2012, since minute differences in estimates are within margins of error; (b) poverty rates also have been unchanged in the full year periods from 2006 to 2012; (c) estimates of the proportion of Filipinos who are poor are lower in the full year, compared to first semester figures, on account of extra income received from thirteenth month wages and bonuses, and other income received in the second semester.
Since poverty rates are unchanged, the number of poor Pinoys is increasing on account of population growth.
But why hasn’t poverty incidence changed?
Changes in poverty rates result, if there is a rise in incomes (in real terms), or if there are changes in income distribution. Between 2009 and 2012, all segments of income distribution had rising incomes, but the rise in incomes was commensurate to the increase in prices.
The poor are not really getting any poorer: their incomes are rising, albeit only as fast as inflation. Regarding income distribution, it can be noted that measures of income inequality, such as the share of the bottom 20% in national income, and the Palma ratio (defined as the ratio of the income of the top 10% to the bottom 40%) have both been unchanged from 2009 to 2012.
Thus, the entire income distribution rate also remains unchanged.
The PSA’s technical notes point out that the source of poverty data in the first half of 2013 is the 2013 Annual Poverty Indicator Survey (APIS), another survey of the PSA, which used a different questionnaire from that of the 2012 FIES.
Table 2. Selected Statistics on Income Distribution and Income Inequality: 2009, and 2012
|AVERAGE (NOMINAL) PER CAPITA INCOME||2009||2012|
|Bottom 20 percent||11,049||12,602|
|Lower Middle 20 percent||18,580||21,203|
|Middle 20 percent||28,108||32,217|
|Upper Middle 20 percent||44,932||51,426|
|Top 20 percent||116,767||132,891|
PShare of Bottom 20% in National Income
|Note: Author’s calculations from the FIES|
Does this suggest that programs such as Pantawid Pamilya, the government’s Conditional Cash Transfer (CCT) program, have failed? Not really. The CCT was designed not as a short-term solution for poverty reduction, but rather a mechanism to assist poor households to break free from intergenerational poverty by investing in the education of their children, and health of their household members.
The effects of Pantawid on poverty are expected to take time, when beneficiary children that have better education and health get into the labor market. Unfortunately, CCT critics and even some Pantawid supporters expect the program to have immediate impact on poverty reduction. The CCT has various positive outcomes on the poor, and this will be discussed in a subsequent article.
Expecting quick changes in poverty because of Pantawid is unrealistic, especially since in 2012 poor families, which have an average family size of 6, needed, on average, P29,765 to cross the poverty line, while CCT beneficiary families only received a maximum of P15,000 grants in 2012 (P300 per child per month for 10 months for a maximum of 3 children, plus P500 per month for twelve months for health support), if they satisfied their co-responsibilities.
So, the CCT cash grants are truly “Pantawid” especially in the wake of disasters and other income shocks. Still, many analysts are convinced that had we implemented Pantawid a decade ago, we would be reaping benefits of lower poverty incidence and lower income inequality today.
In summary, we do not yet have evidence of changes in poverty or income distribution.
Still, this does not suggest that the CCT is not working since cash grants in Pantawid are not enough to help the poor cross the poverty line. The grants are supposed to incentivize the poor into investing in human capital. Also, climate change is a game changer. Blaming gets us nowhere, folks.
Certainly, there are challenges in making economic growth inclusive. We all have to work together. Everyone, especially our taipans, has a role to play in ensuring that no one person is left behind as we pursue economic development. - Rappler.com
Dr. Jose Ramon "Toots" Albert is a professional statistician who has written on poverty measurement, education statistics, agricultural statistics, climate change, macro prudential monitoring, survey design, data mining, and statistical analysis of missing data. He is a Senior Research Fellow of the government’s think tank Philippine Institute for Development Studies, and the president of the country’s professional society of data producers, users and analysts, the Philippine Statistical Association, Inc. for 2014-2015. He finished a PhD in Statistics from the State University of New York at Stony Brook. He is also an elected member of the International Statistical Institute, and of the National Research Council of the Philippines, as well as a Fellow of the Social Weather Stations. From 2012-2014, he served as Secretary General of the now defunct National Statistical Coordination Board and in this position, he explained what statistics mean through his bi-weekly blogs at the NSCB.